code: def test_gemm_transB(datadir):
      model = onnx.load(datadir.file("gemm_not_transB.onnx"))
      model_transB = onnx.load(datadir.file("gemm_transB.onnx"))
      net = load_onnx_neural_network(model)
      net_transB = load_onnx_neural_network(model_transB)
      layers = list(net.layers)
      layers_transB = list(net_transB.layers)
      assert len(layers) == len(layers_transB)
      assert layers[1].weights.shape == layers_transB[1].weights.shape
      assert (
          abs(layers[1].weights[0][0] - layers_transB[1].weights[0][0])
          < 1e-05
      )
      assert (
          abs(layers[1].weights[0][1] - layers_transB[1].weights[1][0])
          < 1e-05
      )
      assert (
          abs(layers[1].weights[1][0] - layers_transB[1].weights[0][1])
          < 1e-05
      )
      assert (
          abs(layers[1].weights[1][1] - layers_transB[1].weights[1][1])
          < 1e-05
      )
  
file_path: OMLT/tests/io/test_onnx_parser.py
imports: import pytest
  from omlt.dependencies import onnx, onnx_available
label_desc: Use image node_id 5 for calling a global function with example usage: test_gemm_transB(datadir) without return types